CN107148026A - A kind of source of radio frequency energy Optimization deployment method energized for body network node - Google Patents
A kind of source of radio frequency energy Optimization deployment method energized for body network node Download PDFInfo
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- 238000009825 accumulation Methods 0.000 claims description 2
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/18—Network planning tools
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- G—PHYSICS
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J50/00—Circuit arrangements or systems for wireless supply or distribution of electric power
- H02J50/20—Circuit arrangements or systems for wireless supply or distribution of electric power using microwaves or radio frequency waves
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- H02J7/025—
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B13/00—Transmission systems characterised by the medium used for transmission, not provided for in groups H04B3/00 - H04B11/00
- H04B13/005—Transmission systems in which the medium consists of the human body
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
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Abstract
A kind of source of radio frequency energy Optimization deployment method energized for body network node, comprises the following steps：The Move Mode of user is modeled as the figure that dwell point and track side are constituted；Iterate to calculate the position of newly-increased energy source, first stage stage by stage according to different object functions, newly-increased energy source causes body network node to be more than energy expenditure power in the charge power of all dwell points；Second stage, newly-increased energy source causes the ceiling capacity on all track sides to accumulate net consumption figures and be no more than node energy-storage travelling wave tube capacity；Phase III, newly-increased energy source make it that outage probability does not meet system requirements to the actual energy of body network node.This method, which is applied to body network node, can capture the scene that RF energy is charged, and can rationally dispose energy source according to the Move Mode of user, meet the energy of system not interrupt request, reduction lower deployment cost.
Description
Technical field
The present invention relates to a kind of source of radio frequency energy Optimization deployment method energized for body network node, this method is applied to catch
Obtain the body area network of RF energy work.
Background technology
With the development of wearable technology and wireless communication technology, intelligent sensing equipment is increasingly being used for human body prison
Survey, these equipment catch various user data, internet high in the clouds are uploaded to whenever and wherever possible, as new Internet of Things web portal.It is this
The wireless network that biology sensor in human body wearable sensors or implantation human body is constituted is referred to as " body area network ", its whole day
Wait online characteristic and make it possible convenient lasting physiology monitor, for example, to the patients' such as heart disease, epilepsy, diabetes
Constant physiological is monitored and early warning.With becoming increasingly popular for implantable smart machine, body area network will combine together with people, as daily
An indispensable part for life.
Traditional body network node is battery powered or periodic charge, it is impossible to realize that network continues non-stop run, especially right
In the application of implantation human body, battery is changed or implantation equipment taking-up charging is costly.Have benefited from wireless energy transmission technology
Breakthrough, the radio wave that body network node can be sent from equipment such as RFID reader, Wi-Fi Hotspot, cellular basestations
In capture energy, to support to sense, calculate and communicate.
The energy capture power of body network node can be effectively improved to making rational planning for for RF energy source position.Due to body domain
Net node deployment need to consider the Move Mode of user in human body, energy source deployment issue.The present invention solve the problem of be how portion
The minimum source of radio frequency energy of administration energizes for body network node so that user's its node energy carried in moving process is difficult hair
It is raw to interrupt.Publication No. CN105550480A, CN105722104A patent document are each provided in the wireless biography of radio frequency charging
Greedy and the energy source dispositions method based on particle group optimizing in sense net, target is so that given position with minimum energy source
The charge power of sensing node be consistently greater than or equal to its energy expenditure power.There is document to consider sensing node moveable
A kind of scene, it is proposed that energy source dispositions method when sensing node is appeared in plane domain with equiprobability, target is to use
Minimum energy source causes the charge power average value of plane domain arbitrfary point to be more than or equal to the energy expenditure work(of sensing node
Rate (referring to《Energy Provisioning in Wireless Rechargeable Sensor Networks》, publish in
IEEE Transactions on Mobile Computing, 2013).But, above method be not particularly suited for the present invention relates to
User there is the scene of specific Move Mode.
The content of the invention
In order to overcome can not adapting to user's Move Mode, energy can not being met for existing RF energy source position planing method
The deficiency that outage probability is not required, the present invention provides one kind and is applied to user's Move Mode, effectively meets energy not outage probability
It is required that for body network node energize source of radio frequency energy Optimization deployment method.
The technical solution adopted for the present invention to solve the technical problems is：
A kind of source of radio frequency energy Optimization deployment method energized for body network node, comprises the following steps：
Step 1 body network node is located at user's body surface or internal, by capturing the wireless communication that periphery source of radio frequency energy is sent
Number energy carries out data acquisition and communication；According to the positional information of the multiple mobile subscribers in certain region in a period of time, pass through cluster
Group of subscribers mobility model is stopped point set V={ v by algorithm with frequent1,v2,...,vNAnd cluster track set E composition have
To figure G=(V, E) descriptions, wherein, N is dwell point number, directed edge ei,j∈ E represent exist in this region from dwell point vi
To dwell point vjMotion track；User is in any dwell point viResidence time t at ∈ V obeys transversal normal distribution, its probability
Density function is0≤t ＜ ∞, wherein, μ and σ2It is average and variance respectively, α is
Regular constant, order To ensure
Deployment region is evenly dividing as X × Y grid by step 2, and sizing grid is determined by required precision and computing capability
Fixed, candidate's deployed position of energy source is set as each net center of a lattice, and can dispose in a grid multiple energy simultaneously
Source；
Step 3 travels through all grids, calculates the first object functional value that energy source is deployed under each grid, increases energy newly
Source is deployed in the grid for causing first object functional value minimum, if being deployed in the first object functional value phase of multiple grids
Deng, then increase newly energy source random placement in one of grid；
Step 4 judges whether the first object functional value under current deployment scheme is 0, if 0, it can guarantee that body network node
It is more than energy expenditure power in the charge power of all dwell points, into step 5；Otherwise, repeat step 3；
Step 5 is for track side ei,j∈ E, it is assumed that its length is li,j, it is classified asBar line segment, Δ l value by
Required precision and computing capability are determined, when length is equal to or less than and moved on Δ l line segment, the body network node that user carries
Charge power keeps constant, is the charge power of line segment central spot；
Step 6 travels through all grids, calculates the second target function value that energy source is deployed under each grid, increases energy newly
Source is deployed in the grid for causing the second target function value minimum, if being deployed in the second target function value phase of multiple grids
Deng, then increase newly energy source random placement in one of grid；
Step 7 judges whether the second target function value under current deployment scheme is 0, if 0, it can guarantee that all track sides
Ceiling capacity accumulate net consumption figures and be no more than node energy-storage travelling wave tube capacity, into step 8；Otherwise, repeat step 6；
Step 8 travels through all grids, calculates the 3rd target function value that energy source is deployed under each grid, increases energy newly
Source is deployed in the grid for causing the 3rd target function value minimum, if being deployed in the 3rd target function value phase of multiple grids
Deng, then increase newly energy source random placement in one of grid；
Step 9 judges whether the 3rd target function value under current deployment scheme is 0, if 0, it can guarantee that body network node
Outage probability does not meet system requirements to actual energy；End operation；Otherwise, repeat step 8.
Further, in the step 3, the first object function expression is：
Wherein, PcThe energy expenditure power of body network node is represented,Represent dwell point viThe charge power at place, if
There is K energy source in current deployment scheme,Calculated and obtained by formula (2)：
Wherein η is rectification efficiency, GsIt is transmission antenna gain, GrIt is receiving antenna gain, LpIt is polarization loss, λ is ripple
Long, ε is regulation parameter, to ensureValue is limited, dk,iIt is k-th of energy source and point viThe distance between, PsIt is energy source
Transmission power,It is the phase offset of radiofrequency signal, | | | | represent to plural modulus therein.
Further, in the step 6, the second object function expression formula is：
Wherein, EcThe energy-storage travelling wave tube capacity of body network node is represented,Represent from dwell point viTo dwell point vjIt is mobile
During ceiling capacity accumulate net consumption figures, calculated and obtained by formula (4)：
WhereinRepresent track side ei,jIn m sections of line segment central point ui,j,mThe charge power at place, can be by formula (2)
Calculating is obtained, li,j,mRepresent track side ei,jIn m sections of line segments length,Represent the average rate travel of user.
Further, in the step 8, the 3rd object function expression formula is：
Wherein, p0Represent body network node the energy not outage probability, p of system requirementsi,jRepresent user from dwell point viTo
Dwell point vjEnergy in moving process not outage probability, is calculated by formula (6) and obtained：
Wherein ti,jRepresent user along track side ei,jIn moving process, at least need stopping to ensure that node energy is not interrupted
Stationary point viLocate residence time, calculated and obtained by formula (7)：
Beneficial effects of the present invention are mainly manifested in：It can capture what RF energy was charged suitable for body network node
Scene, can rationally dispose energy source according to the Move Mode of user, meet the energy of system not interrupt request, and reduction is deployed to
This.
Brief description of the drawings
Fig. 1 is implementing procedure figure of the present invention；
Fig. 2 is the digraph G of user's Move Mode described in the present embodiment schematic diagram；
Fig. 3 is probability density function schematic diagram of the user in the dwell point residence time in the present embodiment.
Embodiment
The invention will be further described below in conjunction with the accompanying drawings.
1~Fig. 3 of reference picture, a kind of source of radio frequency energy Optimization deployment method energized for body network node, including following step
Suddenly：
Step 1 body network node is located at user's body surface or internal, by capturing the wireless communication that periphery source of radio frequency energy is sent
Number energy carries out data acquisition and communication.User generally there are several residence times longer in certain region moving process
Dwell point and some relatively-stationary motion tracks.Therefore, the Move Mode of user is built according to features above first
Mould.According to the positional information of the multiple mobile subscribers in certain region in a period of time, by clustering algorithm by group of subscribers mobility model
Point set V={ v are stopped with frequent1,v2,...,vNAnd digraph G=(V, the E) descriptions that set E in track is constituted are clustered, wherein,
N is dwell point number, directed edge ei,j∈ E represent exist in this region from dwell point viTo dwell point vjMotion track, such as
Shown in Fig. 2；User is in any dwell point viResidence time t at ∈ V obeys transversal normal distribution, as shown in figure 3, its probability is close
Spending function is0≤t ＜ ∞, μ and σ2It is average and variance respectively, α is regular
Change constant, order To ensureAverage
It can be obtained with variance according to the actual duration data of a large number of users through counting calculating.
Deployment region is evenly dividing as X × Y grid by step 2, and candidate's position of energy source is set as each net
Center of a lattice, and multiple energy sources can be disposed simultaneously in a grid, the size of grid is by deployment required precision and calculating energy
Power determines that grid is smaller, and deployment precision is higher, but computation complexity is also higher；
Step 3 ensures that body network node can effectively charge at each dwell point first, i.e., the charge power at each dwell point
More than energy expenditure power.All grids are traveled through, the first object functional value that energy source is deployed under each grid is calculated, increased newly
Energy source is deployed in the grid for causing first object functional value minimum, if being deployed in the first object functional value of multiple grids
It is equal, then energy source random placement is increased newly in one of grid；
Further, in step 3, the first object function expression is：
Wherein, PcThe energy expenditure power of body network node is represented,Represent dwell point viThe charge power at place, if
There is K energy source in current deployment scheme,Calculated and obtained by formula (2)：
Wherein η is rectification efficiency, GsIt is transmission antenna gain, GrIt is receiving antenna gain, LpIt is polarization loss, λ is ripple
Long, ε is regulation parameter, to ensureValue is limited, dk,iIt is k-th of energy source and point viThe distance between, PsIt is energy source
Transmission power,It is the phase offset of radiofrequency signal, | | | | represent to plural modulus therein.In the present embodiment, η
=0.3, Gs=8dBi, Gr=2dBi, Lp=3dB, λ=0.33m, ε=0.2316m, Ps=1~4W；
Step 4 judges whether the first object functional value under current deployment scheme is 0, if 0, it can guarantee that body network node
It is more than energy expenditure power in the charge power of all dwell points, into step 5；Otherwise, repeat step 3；
Step 5 due to energy-storage travelling wave tube finite capacity, therefore user it is mobile on the side of each bar track during ceiling capacity
Net consumption figures is accumulated no more than energy-storage travelling wave tube capacity.Net consumption figures is accumulated in order to calculate ceiling capacity, each track side is carried out
Segmentation.For track side ei,j∈ E, it is assumed that its length is li,j, it is classified asBar line segment, is equal to or less than Δ l in length
Line segment on when moving, the body network node charge power that user carries keeps constant, is the charge power of line segment central spot,
Δ l value is determined that Δ l is smaller, and computational accuracy is higher, but computation complexity is also higher by required precision and computing capability；
Step 6 travels through all grids, calculates the second target function value that energy source is deployed under each grid, increases energy newly
Source is deployed in the grid for causing the second target function value minimum, if being deployed in the second target function value phase of multiple grids
Deng, then increase newly energy source random placement in one of grid；
Further, second object function expression formula is described in step 6：
Wherein, EcThe energy-storage travelling wave tube capacity of body network node is represented,Represent from dwell point viTo dwell point vjIt is moved through
Ceiling capacity in journey accumulates net consumption figures, by formula (4) by calculating user successively by each line segment of a track
The net consumption figures of energy accumulation takes maximum to be worth to：
WhereinRepresent track side ei,jIn m sections of line segment central spots charge power, can be calculated by formula (2)
Obtain, li,j,mRepresent track side ei,jIn m sections of line segments length,The average rate travel of user is represented, can be according to a large number of users
Rate travel data, through count calculating obtain.
Step 7 judges whether the second target function value under current deployment scheme is 0, if 0, it can guarantee that all track sides
Ceiling capacity accumulate net consumption figures and be no more than node energy-storage travelling wave tube capacity, into step 8；Otherwise, repeat step 6；
Outage probability need to not meet system requirements to the actual energy of step 8 body network node.All grids are traveled through, energy is calculated
Amount source is deployed in the 3rd target function value under each grid, and newly-increased energy source is deployed in cause the 3rd target function value minimum
In grid, if the 3rd target function value for being deployed in multiple grids is equal, energy source random placement is increased newly in one of them
In grid；
Further, the 3rd object function expression formula is described in step 8：
Wherein, p0Represent body network node the energy not outage probability, p of system requirementsi,jRepresent user from dwell point viTo
Dwell point vjEnergy in moving process not outage probability, is calculated by formula (6) and obtained：
Wherein ti,jRepresent user along track side ei,jIn moving process, at least need stopping to ensure that node energy is not interrupted
Stationary point viLocate residence time, calculated and obtained by formula (7)：
Step 9 judges whether the 3rd target function value under current deployment scheme is 0, if 0, it can guarantee that body network node
Outage probability does not meet system requirements, end operation to actual energy；Otherwise, repeat step 8.
Claims (4)
1. a kind of source of radio frequency energy Optimization deployment method energized for body network node, it is characterised in that：Comprise the following steps：
Step 1 body network node is located at user's body surface or internal, by capturing the wireless signal energy that periphery source of radio frequency energy is sent
Amount carries out data acquisition and communication；According to the positional information of the multiple mobile subscribers in certain region in a period of time, pass through clustering algorithm
By group of subscribers mobility model frequently stop point set V={ v1,v2,...,vNAnd cluster track set E composition digraph
G=(V, E) is described, wherein, N is dwell point number, directed edge ei,j∈ E represent exist in this region from dwell point viTo stopping
Stationary point vjMotion track；User is in any dwell point viResidence time t at ∈ V obeys transversal normal distribution, its probability density
Function isWherein, μ and σ2It is average and variance respectively, α is
Regular constant, order To ensure
Deployment region is evenly dividing as X × Y grid by step 2, and sizing grid is determined by required precision and computing capability, energy
Candidate's deployed position in amount source is set as each net center of a lattice, and can dispose in a grid multiple energy sources simultaneously；
Step 3 travels through all grids, calculates the first object functional value that energy source is deployed under each grid, increases energy source portion newly
Affix one's name in the minimum grid of first object functional value is caused, if the first object functional value for being deployed in multiple grids is equal,
Newly-increased energy source random placement is in one of grid；
Step 4 judges whether the first object functional value under current deployment scheme is 0, if 0, it can guarantee that body network node in institute
The charge power for having dwell point is more than energy expenditure power, into step 5；Otherwise, repeat step 3；
Step 5 is for track side ei,j∈ E, it is assumed that its length is li,j, it is classified asBar line segment, Δ l value is by precision
It is required that determined with computing capability, when length is equal to or less than and moved on Δ l line segment, the body network node charging that user carries
Power keeps constant, is the charge power of line segment central spot；
Step 6 travels through all grids, calculates the second target function value that energy source is deployed under each grid, increases energy source portion newly
Affix one's name in the minimum grid of the second target function value is caused, if the second target function value for being deployed in multiple grids is equal,
Newly-increased energy source random placement is in one of grid；
Step 7 judges whether the second target function value under current deployment scheme is 0, if 0, it can guarantee that all track sides most
The net consumption figures of big energy accumulation is no more than node energy-storage travelling wave tube capacity, into step 8；Otherwise, repeat step 6；
Step 8 travels through all grids, calculates the 3rd target function value that energy source is deployed under each grid, increases energy source portion newly
Affix one's name in the minimum grid of the 3rd target function value is caused, if the 3rd target function value for being deployed in multiple grids is equal,
Newly-increased energy source random placement is in one of grid；
Step 9 judges whether the 3rd target function value under current deployment scheme is 0, if 0, it can guarantee that body network node is actual
Energy outage probability does not meet system requirements, end operation；Otherwise, repeat step 8.
2. a kind of source of radio frequency energy Optimization deployment method energized for body network node as claimed in claim 1, its feature exists
In：In the step 3, the first object function expression is：
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Wherein, PcThe energy expenditure power of body network node is represented,Represent dwell point viThe charge power at place, if currently
There is K energy source in deployment scheme,Calculated and obtained by formula (2)：
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Wherein η is rectification efficiency, GsIt is transmission antenna gain, GrIt is receiving antenna gain, LpIt is polarization loss, λ is wavelength, and ε is
Regulation parameter, to ensureValue is limited, dk,iIt is k-th of energy source and point viThe distance between, PsIt is the transmitting of energy source
Power,It is the phase offset of radiofrequency signal, | | | | represent to plural modulus therein.
3. a kind of source of radio frequency energy Optimization deployment method energized for body network node as claimed in claim 1 or 2, its feature
It is：In the step 6, the second object function expression formula is：
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Wherein, EcThe energy-storage travelling wave tube capacity of body network node is represented,Represent from dwell point viTo dwell point vjIn moving process
Ceiling capacity accumulate net consumption figures, calculated and obtained by formula (4)：
WhereinRepresent track side ei,jIn m sections of line segment central point ui,j,mThe charge power at place, can be calculated by formula (2)
Obtain, li,j,mRepresent track side ei,jIn m sections of line segments length,Represent the average rate travel of user.
4. a kind of source of radio frequency energy Optimization deployment method energized for body network node as claimed in claim 1 or 2, its feature
It is：In the step 8, the 3rd object function expression formula is：
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<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
<mo>&Element;</mo>
<mi>E</mi>
</mrow>
</munder>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
<mo>{</mo>
<msub>
<mi>p</mi>
<mn>0</mn>
</msub>
<mo>-</mo>
<msub>
<mi>p</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
<mo>,</mo>
<mn>0</mn>
<mo>}</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>5</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, p0Represent body network node the energy not outage probability, p of system requirementsi,jRepresent user from dwell point viTo stop
Point vjEnergy in moving process not outage probability, is calculated by formula (6) and obtained：
<mrow>
<msub>
<mi>p</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
<mo>=</mo>
<mi>P</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>&GreaterEqual;</mo>
<msub>
<mi>t</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msubsup>
<mo>&Integral;</mo>
<msub>
<mi>t</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
<mi>&infin;</mi>
</msubsup>
<mfrac>
<mn>1</mn>
<mrow>
<msqrt>
<mrow>
<mn>2</mn>
<mi>&pi;</mi>
</mrow>
</msqrt>
<mi>&alpha;</mi>
<mi>&sigma;</mi>
</mrow>
</mfrac>
<mi>exp</mi>
<mo>(</mo>
<mrow>
<mo>-</mo>
<mfrac>
<msup>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>-</mo>
<mi>&mu;</mi>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mrow>
<mn>2</mn>
<msup>
<mi>&sigma;</mi>
<mn>2</mn>
</msup>
</mrow>
</mfrac>
</mrow>
<mo>)</mo>
<mi>d</mi>
<mi>t</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>6</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein ti,jRepresent user along track side ei,jIn moving process, at least needed in dwell point to ensure that node energy is not interrupted
viLocate residence time, calculated and obtained by formula (7)：
<mrow>
<msub>
<mi>t</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mfrac>
<msubsup>
<mi>E</mi>
<mi>r</mi>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mrow>
<msubsup>
<mi>P</mi>
<mi>h</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>v</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
</msubsup>
<mo>-</mo>
<msub>
<mi>P</mi>
<mi>c</mi>
</msub>
</mrow>
</mfrac>
</mtd>
<mtd>
<mrow>
<msubsup>
<mi>E</mi>
<mi>r</mi>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>></mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mn>0</mn>
</mtd>
<mtd>
<mrow>
<msubsup>
<mi>E</mi>
<mi>r</mi>
<mrow>
<mo>(</mo>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
<mo>)</mo>
</mrow>
</msubsup>
<mo>&le;</mo>
<mn>0</mn>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>7</mn>
<mo>)</mo>
</mrow>
<mo>.</mo>
</mrow>
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| CN110167177A (en) * | 2019-05-21 | 2019-08-23 | 河南科技大学 | Wireless body area network collaboration communication transmission method based on dynamic time slot allocation |
| CN111277951A (en) * | 2020-02-13 | 2020-06-12 | 南京邮电大学 | Greedy submodule-based wireless chargeable sensor network charger deployment method |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107995632A (en) * | 2017-11-06 | 2018-05-04 | 浙江工业大学 | A kind of passive sensing node deployment dispatching method for ensureing static object detection quality |
| CN107995632B (en) * | 2017-11-06 | 2021-06-18 | 浙江工业大学 | Passive sensing node deployment scheduling method for ensuring static target detection quality |
| CN110167177A (en) * | 2019-05-21 | 2019-08-23 | 河南科技大学 | Wireless body area network collaboration communication transmission method based on dynamic time slot allocation |
| CN110167177B (en) * | 2019-05-21 | 2023-01-31 | 河南科技大学 | Wireless body area network cooperative communication transmission method based on dynamic time slot allocation |
| CN111277951A (en) * | 2020-02-13 | 2020-06-12 | 南京邮电大学 | Greedy submodule-based wireless chargeable sensor network charger deployment method |
| CN111277951B (en) * | 2020-02-13 | 2021-04-06 | 南京邮电大学 | Greedy submodule-based wireless chargeable sensor network charger deployment method |
| CN113810138A (en) * | 2021-09-24 | 2021-12-17 | 重庆邮电大学 | Multipath channel modeling method for dynamic on-body channel in wireless body area network |
| CN113810138B (en) * | 2021-09-24 | 2023-06-30 | 重庆邮电大学 | Multipath channel modeling method for dynamic on-body channel in wireless body area network |
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